The essential role of non-coding RNAs (ncRNAs) in cardiovascular disease (CVD) research instigates a shift from empirical studies to those based on molecular mechanisms, targeted interventions, and personalized health management in the world of precision medicine. This review systematically summarizes the expression profiles and multilayered regulatory mechanisms of various ncRNAs such as microRNAs (miRNAs), long non-coding RNAs (lncRNAs), circular RNAs (circRNAs), and small nucleolar RNAs (snoRNAs) in a variety of cardiovascular diseases (CVDs) ranging from congenital heart disease to atherosclerosis (AS), cardiomyopathies, heart failure (HF), and arrhythmias. The central roles of key pathological pathways like epigenetic changes, competing endogenous RNA (ceRNA), inflammation and cell fate determination will be highlighted. From a diagnostic point of view, ncRNAs have good potentials as early-stage biomarkers, in applications such as exosomal liquid biopsy, disease classification, and prognosis. Emerging technologies, notably locked nucleic acid (LNA) oligonucleotides, adeno-associated virus serotype 9 (AAV9)-based delivery systems and engineered exosomes, are unlocking new avenues for intervention on the therapeutic front. These developments, coupled with drug repurposing strategies and tissue-specific delivery platforms, can make ncRNA-targeted therapies more specific and controllable. At the same time, interdisciplinary innovations, like single-cell multi-omics, spatial transcriptomics, CRISPR-dCas9 systems, and deep learning assist clinical translation greatly. However, the real-world application of ncRNA-based therapies is constrained by many challenges like low delivery efficiency, functional redundancy, and microenvironmental dependence. Future directions must aim to create integrative platforms that can dynamically identify and modulate ncRNA functions to link mechanistic studies to personalized therapies and subsequently expedite clinical translation of ncRNA discoveries. In this sense, three cross-scale principles-network topology and ceRNA competition dynamics; spatiotemporal gradients modeled by exosome transport and tissue microenvironments; and energetic/stoichiometric constraints like Dicer processing capacity and miRNA-target ratios- provide an analytical framework that appears recurrently across diverse CVD phenotypes and tighten the mechanistic unity of this review.
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